{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### An example showing the plot_elbow_curve method used by a scikit-learn clusterer\n",
    "\n",
    "In this example, we'll be plotting an elbow curve for our k-means clusterer on the Iris dataset. We'll first create an instance of `KMeans` from scikit-learn, and then feed that to our `scikitplot.cluster.plot_elbow_curve` method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "from __future__ import absolute_import\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.datasets import load_iris as load_data\n",
    "\n",
    "# Import scikit-plot\n",
    "import scikitplot as skplt\n",
    "\n",
    "%pylab inline\n",
    "pylab.rcParams['figure.figsize'] = (14, 14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the data\n",
    "X, y = load_data(return_X_y=True)\n",
    "\n",
    "# Create clusterer instance\n",
    "kmeans = KMeans(random_state=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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wJGnjjo1MnwQA7LcFtQv07pp3+bsEe0R5i1N+f/Aj5Q3YPyNKR2ji6Ikxe79V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LAAAZ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\nSZKkKmB4kyRJkqQq8P8BU9IgoskFuQIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22f032752b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot!\n",
    "skplt.cluster.plot_elbow_curve(kmeans, X, cluster_ranges=range(1, 11))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
